The present invention relates to financial risk prediction systems (FRPS). More particularly, the present invention relates to improved methods and apparatus for a transaction-based risk prediction system that advantageously assess the financial risk level associated with an account and/or an account holder based on the account holder""s transaction pattern and/or transactions pertaining to that account holder across multiple accounts and/or account issuers.
In recent years, account issuers (e.g., banks, credit unions, mortgage companies, and the like) have significantly increased the types and volumes of accounts issued to account holders. A typical account holder (e.g., an individual or business account holder) nowadays may be issued, for example, multiple charge (credit) accounts, one or more mortgages, multiple revolving accounts, and/or one or more installment payment plans. For a majority of account holders, good financial planning results in financial stability and solvency. There are, however, a significant percentage of account holders who, for various reasons (e.g., unanticipated changes in life""s circumstances, credit abuse, or even fraud), do not live up to the obligations they incurred to account issuers.
When account holders default (e.g., simply refuse to pay the amount owed or declare bankruptcy altogether), account issuers may at times be forced to resort to costly collection procedures and/or to write off the amounts owed altogether. As can be appreciated from the foregoing, when an account holder declares bankruptcy for example, the amount lost may be substantial since most or all credit accounts (charge/credit accounts, mortgages, revolving accounts, installment payment plans, and/or others) may be discharged under bankruptcy laws. The losses increase, for example, the cost of credit to all current and potential account holders, including those having satisfactory credit histories.
To minimize losses, account issuers have constantly been searching for ways to predict in advance accounts and/or account holders who are at risk for credit default and/or fraud. By way of example, account issuers routinely employ credit bureaus, essentially data collection services, to ascertain whether an applicant for new or additional credit is sufficiently credit-worthy for the type of account and amount that he is applying for. If an applicant wishes to apply for a Visa credit card account, for example, a potential issuing bank may request a credit report on the applicant from one or more credit bureaus to ascertain whether the applicant has a satisfactory credit history, adequate income, reasonable debt-to-income ratio, and the like, before deciding whether the applicant should be approved for the credit account and what the appropriate credit limit should be.
To facilitate the management of accounts, account issuers may employ scores developed by credit bureaus. These scores may, for example, be utilized to assist in some aspects of account management, e.g., in the account issuer""s decision to increase or decrease the current limit.
Although the use of credit bureaus eliminates some financial risk, there are disadvantages. For example, it is known that not all account issuers report to credit bureaus. Some account issuers may choose to report only to a selected credit bureau but not another, making it difficult for an account issuer to efficiently obtain a complete credit history pertaining to a particular applicant.
Still further, it is widely known that credit bureau data is prone to error. The errors may arise from delayed or inaccurate delivery of the account holder""s payment to the account issuers, through inaccurate data entry of the part of the account issuers, through erroneous reporting by the account issuers, and/or inaccurate data processing by the credit bureaus themselves. Accordingly, it is not uncommon for individuals who are objectively poor financial risks to be given satisfactory scores by the credit bureaus, and vice versa.
Most significantly, credit bureau data typically pertains only to account data, e.g., account types, account limits, and historical payment information. As such, the data kept by credit bureaus is significantly dated since data from the various account issuers is typically not updated with the credit bureaus until after the end of each billing cycle (which may be, for example, monthly or quarterly). Accordingly, the credit bureaus typically do not have accurate or adequate data pertaining to the credit performance of a particular account holder in between reporting periods. Since credit bureau scores are not based on financial transaction data, a credit bureau would not be able to, for example, warn account issuers that certain accounts and/or account holders are at risk based on the recent transactions.
The credit bureaus do not have the ability to ascertain transaction pattern to warn account issuers of potential financial risks. If, for example, an individual intends to commit credit abuse, fraud, and/or to file bankruptcy in the near future, a credit bureau would not be able to know and to issue warnings to account issuers that this individual has, in the last few days, systematically and in an uncharacteristic manner, used up his credit of his charge accounts. In fact, the credit bureaus may continue to assign satisfactory scores to that individual (thereby enabling that individual to continue making purchases on credit, obtaining additional credit and/or opening additional credit accounts) until the account holder misses one or more billing cycles and/or files for bankruptcy.
The account issuers themselves also developed techniques to gauge the credit worthiness of a particular potential or current account holder based on how that account holder pays on an account. By way of example, behavioral scoring systems may be employed to monitor the payment performance of an account (e.g., by monitoring the payment data and the relationship between credit line and balance) in their assessment of an individual""s credit worthiness. However, since the payment performance of an account is updated only per billing cycle, this technique also typically does not provide adequate warnings pertaining to the financial risk of a particular account holder based on activities occurring in more recent history. By way of example, if an account holder""s past payment performance on an account has been satisfactory, he may, in the last few days, use up substantially all the available credit of one or more accounts (thereby putting him at a higher financial risk) without triggering an alert from the account issuers"" payment-based scoring systems.
Some account issuers or third party processors may be able to, for example, utilize transaction data on a specific account to assess risk with respect to that account. By way of example, account issuers or third party processors may employ rule-based systems to flag accounts having transactions exceeding a certain dollar amount within a predefined period. If, for example, an account holder withdraws more than $3000.00 in cash in one month from a particular account, the rule-based system may flag that account for future investigation.
Furthermore, since account issuers do not typically share financial data pertaining to account holders (due to, e.g., competitive or legal reasons), it is not possible for an account issuer to know that a particular account holder has incurred, in the time interval since the last billing cycle, significant credit obligations to another account issuer. Accordingly, even if a particular account holder may be known to one account issuer to have a higher financial risk since the last billing cycle, this important piece of information is unavailable to the credit bureaus until the end of the current billing period. Accordingly, this knowledge is denied to other account issuers until at least the end of the billing period, rendering their credit lines unduly vulnerable.
Because of the shortcomings of existing behavioral scoring systems, it is possible for an account holder to, in preparation for bankruptcy filing, charge up his various credit accounts with different account issuers substantially undetected. In fact, it has been found that up to 40% of credit accounts involved in bankruptcy filings still have charging privileges. The inability of prior art financial risk monitoring techniques to timely provide warnings pertaining to abusive credit practice to the account issuers creates not only financial losses to the account issuers but also a loss of confidence in the minds of the consuming public.
In view of the foregoing, there are desired improved financial risk prediction systems and methods therefor which minimize financial losses to the account issuers and/or account holders. The improved financial risk prediction system preferably employs data that facilitates timely warnings of potential financial risks to the account issuers to enable the account issuers to take steps in time to minimize further financial losses. The improved financial risk prediction technique more preferably provides the aforementioned timely warnings at the account holder level, thereby advantageously enabling a given account issuer to ascertain the credit-worthiness of a particular account holder and to take steps to protect outstanding credit lines even if, for example, the financial risk is assessed on transactions performed on accounts belonging to other account issuers.
The invention relates, in one embodiment, to a computer-implemented method for predicting financial risk, which includes receiving transaction data pertaining to a plurality of transactions for a financial account, the transaction data including one of a transaction type and a transaction amount for each of the plurality of transactions. The method further includes scoring the transaction data, including a transaction pattern ascertained from the transaction data, based on a preexisting model to form a score for the financial account. The method further includes transmitting, if the score is below a predefined financial risk threshold, the score to an account issuer of the financial account.
In another embodiment, the invention relates to a computer-implemented method for predicting financial risk, which includes receiving first transaction data pertaining to transactions performed on a first financial account. The first financial account represents a financial account issued to a given account holder by a first account issuer. The method further includes receiving second transaction data pertaining to transaction performed on a second financial account different from the first financial account. The second financial account represents a financial account issued to the given account holder by a second account issuer different from the first account issuer. There is further included scoring the first transaction data and the second transaction data based on a preexisting model to form a score for the account holder. Additionally, there is included transmitting, if the score is below a predefined financial risk threshold, the score to one of the first account issuer and the second account issuer.